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Quantifying spatial and temporal variations in optimal tilt angle of a solar collector relative to a horizontal position assists in maximizing its performance for energy collection depending on changes in time and space. In this study, optimal tilt angles were quantified for solar

Quantifying spatial and temporal variations in optimal tilt angle of a solar collector relative to a horizontal position assists in maximizing its performance for energy collection depending on changes in time and space. In this study, optimal tilt angles were quantified for solar collectors based on the monthly global and diffuse solar radiation on a horizontal surface across Turkey. The dataset of monthly average daily global solar radiation was obtained from 158 places, and monthly diffuse radiation data were estimated using an empirical model in the related literature. Our results showed that high tilt angles during the autumn (September to November) and winter (December to February) and low tilt angles during the summer (March to August) enabled the solar collector surface to absorb the maximum amount of solar radiation. Monthly optimum tilt angles were estimated devising a sinusoidal function of latitude and day of the year, and their validation resulted in a high R2 value of 98.8%, with root mean square error (RMSE) of 2.06o.
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This work presents a new approach with details on the integrated platform and hardware architecture for nanorobots application in epidemic control, which should enable real time in vivo prognosis of biohazard infection. The recent developments in the field of nanoelectronics, with transducers progressively

This work presents a new approach with details on the integrated platform and hardware architecture for nanorobots application in epidemic control, which should enable real time in vivo prognosis of biohazard infection. The recent developments in the field of nanoelectronics, with transducers progressively shrinking down to smaller sizes through nanotechnology and carbon nanotubes, are expected to result in innovative biomedical instrumentation possibilities, with new therapies and efficient diagnosis methodologies. The use of integrated systems, smart biosensors, and programmable nanodevices are advancing nanoelectronics, enabling the progressive research and development of molecular machines. It should provide high precision pervasive biomedical monitoring with real time data transmission. The use of nanobioelectronics as embedded systems is the natural pathway towards manufacturing methodology to achieve nanorobot applications out of laboratories sooner as possible. To demonstrate the practical application of medical nanorobotics, a 3D simulation based on clinical data addresses how to integrate communication with nanorobots using RFID, mobile phones, and satellites, applied to long distance ubiquitous surveillance and health monitoring for troops in conflict zones. Therefore, the current model can also be used to prevent and save a population against the case of some targeted epidemic disease.
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Nowadays, there is a growing interest in applications of space remote sensing systems for maritime surveillance which includes among others traffic surveillance, maritime security, illegal fisheries survey, oil discharge and sea pollution monitoring. Within the framework of several French and European projects, an

Nowadays, there is a growing interest in applications of space remote sensing systems for maritime surveillance which includes among others traffic surveillance, maritime security, illegal fisheries survey, oil discharge and sea pollution monitoring. Within the framework of several French and European projects, an algorithm for automatic ship detection from SPOT-5 HRG data was developed to complement existing fishery control measures, in particular the Vessel Monitoring System. The algorithm focused on feature-based analysis of satellite imagery. Genetic algorithms and Neural Networks were used to deal with the feature-borne information. Based on the described approach, a first prototype was designed to classify small targets such as shrimp boats and tested on panchromatic SPOT-5, 5-m resolution product taking into account the environmental and fishing context. The ability to detect shrimp boats with satisfactory detection rates is an indicator of the robustness of the algorithm. Still, the benchmark revealed problems related to increased false alarm rates on particular types of images with a high percentage of cloud cover and a sea cluttered background.
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This paper presents the analysis of the electromyographic signals from rat stomaches to identify and classify contractions. The results were validated with both visual identification and an ultrasonic system to guarantee the reference. Some parameters were defined and associated to the energy of

This paper presents the analysis of the electromyographic signals from rat stomaches to identify and classify contractions. The results were validated with both visual identification and an ultrasonic system to guarantee the reference. Some parameters were defined and associated to the energy of the signal in frequency domain and grouped in a P vector. The parameters were statistically analyzed and according to the results, an artificial neuronal network was designed to use the P vectors as inputs to classify the electrical signals related to the contraction conditions. A first approach classification was performed with and without contraction classes (CR and NCR), then the same database were subdivided in four classes: with induced contraction (ICR), spontaneous contraction (SCR), without contraction due a post mortem condition (PMR) or under physiological conditions (PNCR). In a two-class classifier, performance was 86%, 93% and 91% of detections for each electrogastromyografic (EGMG) signal from each of three pairs of electrodes considered. Because in the four-class classifier, enough data was not collected for the first pair, then a three-class classifier with 82% of performance was used. For the other two EGMG signals electrode pairs, performance was of 76% and 86% respectively. Based in the results, the analysis of P vectors could be used as a contraction detector in motility studies due to different stimuli in a rat model.
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Signals from Global Navigation Satellite Systems (GNSS) were originally conceived for position and speed determination, but they can be used as signals of opportunity as well. The reflection process over a given surface modifies the properties of the scattered signal, and therefore, by

Signals from Global Navigation Satellite Systems (GNSS) were originally conceived for position and speed determination, but they can be used as signals of opportunity as well. The reflection process over a given surface modifies the properties of the scattered signal, and therefore, by processing the reflected signal, relevant geophysical data regarding the surface under study (land, sea, ice…) can be retrieved. In essence, a GNSS-R receiver is a multi-channel GNSS receiver that computes the received power from a given satellite at a number of different delay and Doppler bins of the incoming signal. The first approaches to build such a receiver consisted of sampling and storing the scattered signal for later post-processing. However, a real-time approach to the problem is desirable to obtain immediately useful geophysical variables and reduce the amount of data. The use of FPGA technology makes this possible, while at the same time the system can be easily reconfigured. The signal tracking and processing constraints made necessary to fully design several new blocks. The uniqueness of the implemented system described in this work is the capability to compute in real-time Delay-Doppler maps (DDMs) either for four simultaneous satellites or just one, but with a larger number of bins. The first tests have been conducted from a cliff over the sea and demonstrate the successful performance of the instrument to compute DDMs in real-time from the measured reflected GNSS/R signals. The processing of these measurements shall yield quantitative relationships between the sea state (mainly driven by the surface wind and the swell) and the overall DDM shape. The ultimate goal is to use the DDM shape to correct the sea state influence on the L-band brightness temperature to improve the retrieval of the sea surface salinity (SSS).
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The objective of the current study was to analyze the seasonal effect on differentiating tree species in an urban environment using multi-temporal hyperspectral data, Light Detection And Ranging (LiDAR) data, and a tree species database collected from the field. Two Airborne Imaging Spectrometer

The objective of the current study was to analyze the seasonal effect on differentiating tree species in an urban environment using multi-temporal hyperspectral data, Light Detection And Ranging (LiDAR) data, and a tree species database collected from the field. Two Airborne Imaging Spectrometer for Applications (AISA) hyperspectral images were collected, covering the Summer and Fall seasons. In order to make both datasets spatially and spectrally compatible, several preprocessing steps, including band reduction and a spatial degradation, were performed. An object-oriented classification was performed on both images using training data collected randomly from the tree species database. The seven dominant tree species (Gleditsia triacanthos, Acer saccharum, Tilia Americana, Quercus palustris, Pinus strobus and Picea glauca) were used in the classification. The results from this analysis did not show any major difference in overall accuracy between the two seasons. Overall accuracy was approximately 57% for the Summer dataset and 56% for the Fall dataset. However, the Fall dataset provided more consistent results for all tree species while the Summer dataset had a few higher individual class accuracies. Further, adding LiDAR into the classification improved the results by 19% for both fall and summer. This is mainly due to the removal of shadow effect and the addition of elevation data to separate low and high vegetation.
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The spatial resolution of a conventional imaging lidar system is constrained by the diffraction limit of the telescope’s aperture. The combination of the lidar and synthetic aperture (SA) processing techniques may overcome the diffraction limit and pave the way for a higher resolution

The spatial resolution of a conventional imaging lidar system is constrained by the diffraction limit of the telescope’s aperture. The combination of the lidar and synthetic aperture (SA) processing techniques may overcome the diffraction limit and pave the way for a higher resolution air borne or space borne remote sensor. Regarding the lidar transmitting frequency modulation continuous-wave (FMCW) signal, the motion during the transmission of a sweep and the reception of the corresponding echo were expected to be one of the major problems. The given modified Omega-K algorithm takes the continuous motion into account, which can compensate for the Doppler shift induced by the continuous motion efficiently and azimuth ambiguity for the low pulse recurrence frequency limited by the tunable laser. And then, simulation of Phase Screen (PS) distorted by atmospheric turbulence following the von Karman spectrum by using Fourier Transform is implemented in order to simulate turbulence. Finally, the computer simulation shows the validity of the modified algorithm and if in the turbulence the synthetic aperture length does not exceed the similar coherence length of the atmosphere for SAIL, we can ignore the effect of the turbulence.
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This article presents the development of a system integrated to a ZigBee network to measure whole-body vibration. The developed system allows distinguishing human vibrations of almost 400Hz in three axes with acceleration of almost 50g. The tests conducted in the study ensured the

This article presents the development of a system integrated to a ZigBee network to measure whole-body vibration. The developed system allows distinguishing human vibrations of almost 400Hz in three axes with acceleration of almost 50g. The tests conducted in the study ensured the correct functioning of the system for the project’s purpose.
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In the paper we utilized the adsorptive transfer stripping differential pulse voltammetry Brdicka reaction for the determination of metallothioneins (MT) in melanoma cells, animal melanoma tissues (MeLiM miniature pig) and blood serum of patients with malignant melanoma. Primarily we attempted to investigate the

In the paper we utilized the adsorptive transfer stripping differential pulse voltammetry Brdicka reaction for the determination of metallothioneins (MT) in melanoma cells, animal melanoma tissues (MeLiM miniature pig) and blood serum of patients with malignant melanoma. Primarily we attempted to investigate the influence of dilution of real sample on MT electrochemical response. Dilution of samples of 1 000 times was chosen the most suitable for determination of MT level in biological samples. Then we quantified the MT level in the melanoma cells, the animal melanoma tissues and the blood serum samples. The MT content in the cells varied within the range from 4.2 to 11.2 μM. At animal melanoma tissues (melanomas localized on abdomen, back limb and dorsum) the highest content of MT was determined in the tumour sampled on the back of the animal and was nearly 500 μg of MTs per gram of a tissue. We also quantified content of MT in metastases, which was found in liver, spleen and lymph nodes. Moreover the average MT level in the blood serum samples from patients with melanoma was 3.0 ± 0.8 μM. MT levels determined at melanoma samples were significantly (p < 0.05) higher compared to control ones at cells, tissues and blood serum.
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This study was executed to determine the plant species of herbaceous cover in a skid road subjected to soil compaction due to timber skidding in a beech (Fagus orientalis Lipsky.) stand. Our previous studies have shown that ground based timber skidding destroys

This study was executed to determine the plant species of herbaceous cover in a skid road subjected to soil compaction due to timber skidding in a beech (Fagus orientalis Lipsky.) stand. Our previous studies have shown that ground based timber skidding destroys the soils extremely, and degradations on ecosystem because of the timber skidding limit recovery and growth of plant cover on skid roads. However, some plant species show healthy habitat, recovery and they can survive after the extreme degradation in study area. We evaluated composition of these plant species and their cover-abundance scales in 100 m x 3 m transect. 15 plant species were determined belongs to 12 plant families and Liliaceae was the highest representative plant family. Smilax aspera L., Epimedium pubigerum (DC.) Moren et Decaisne, Carex distachya Desf. var. distachya Desf., Pteridium aquilinum (L.) Kuhn., Trachystemon orientalis (L.) G. Don, Hedera helix L. have the highest coverabundance scale overall of determined species on compacted skid road.
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The U.S. National Landcover Dataset (NLCD) and the U.S National Elevation Dataset (NED) (bare earth elevations) were used in an attempt to assess to what extent the directional and slope dependency of the Shuttle Radar Topography Mission (SRTM) finished digital elevation model is

The U.S. National Landcover Dataset (NLCD) and the U.S National Elevation Dataset (NED) (bare earth elevations) were used in an attempt to assess to what extent the directional and slope dependency of the Shuttle Radar Topography Mission (SRTM) finished digital elevation model is affected by landcover. Four landcover classes: forest, shrubs, grass and snow cover, were included in the study area (Humboldt Range in NW portion of Nevada, USA). Statistics, rose diagrams, and frequency distributions of the elevation differences (NED-SRTM) per landcover class per geographic direction were used. The decomposition of elevation differences on the basis of aspect and slope terrain classes identifies a) over-estimation of elevation by the SRTM instrument along E, NE and N directions (negative elevation difference that decreases linearly with slope) while b) underestimation is evident towards W, SW and S directions (positive elevation difference increasing with slope). The aspect/slope/landcover elevation differences modelling overcome the systematic errors evident in the SRTM dataset and revealed vegetation height information and the snow penetration capability of the SRTM instrument. The linear regression lines per landcover class might provide means of correcting the systematic error (aspect/slope dependency) evident in SRTM dataset.
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A novel uncalibrated CMOS programmable temperature switch with high temperature accuracy is presented. Its threshold temperature Tth can be programmed by adjusting the ratios of width and length of the transistors. The operating principles of the temperature switch circuit is theoretically explained.

A novel uncalibrated CMOS programmable temperature switch with high temperature accuracy is presented. Its threshold temperature Tth can be programmed by adjusting the ratios of width and length of the transistors. The operating principles of the temperature switch circuit is theoretically explained. A floating gate neural MOS circuit is designed to compensate automatically the threshold temperature Tth variation that results form the process tolerance. The switch circuit is implemented in a standard 0.35 μm CMOS process. The temperature switch can be programmed to perform the switch operation at 16 different threshold temperature Tths from 45－120°C with a 5°C increment. The measurement shows a good consistency in the threshold temperatures. The chip core area is 0.04 mm2 and power consumption is 3.1 μA at 3.3V power supply. The advantages of the temperature switch are low power consumption, the programmable threshold temperature and the controllable hysteresis.
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In the present paper potato plants were cultivated in the presence of ammonium sulphate or elemental sulphur supplementation into the soil to reveal the effects of different sulphur forms on content of nitrogen, phosphorus, potassium, calcium, magnesium and sulphur, and yield of tubers.

In the present paper potato plants were cultivated in the presence of ammonium sulphate or elemental sulphur supplementation into the soil to reveal the effects of different sulphur forms on content of nitrogen, phosphorus, potassium, calcium, magnesium and sulphur, and yield of tubers. During the investigation of the influence of different sulphur forms on yield of potato tubers we did not observe significant changes. Average weight of tubers of control plants per one experimental pot was 355 g. Application of sulphur in both forms resulted in moderate potato tubers weight reduction per one experimental pot compared to control group; average value ranged from 320 to 350 g per one experimental pot. Further we treated the plants with two different supplementation of sulphur with cadmium(II) ions (4 mg of cadmium(II) acetate per kilogram of the soil). The significantly lowest cadmium content (p < 0.05) was determined in tissues of plants treated with the highest dosage of elemental sulphur (0.64 mg Cd/kg) compared to control plants (0.82 mg Cd/kg). We also aimed our attention on the cadmium content in proteins, lipids or soluble carbohydrates and ash. Application of sulphate as well as elemental sulphur resulted in significant cadmium content reduction in lipid fraction compared to control plants. In addition to this we quantified content of low molecular mass thiols in potatoes tissues. To determine the thiols content we employed differential pulse voltammetry Brdicka reaction. After twelve days of the treatment enhancing of thiols level was observed in all experimental groups regardless to applied sulphur form and its concentration. Finally we evaluated the effect of sulphur supplementation on Phytophora infestans infection of potato plants.
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Airborne multispectral and hyperspectral remote sensing is a powerful tool for environmental monitoring applications. In this paper we describe a new system (ASPIS) composed by a 4-CCD spectral sensor, a thermal IR camera and a laser altimeter that is mounted on a flexible

Airborne multispectral and hyperspectral remote sensing is a powerful tool for environmental monitoring applications. In this paper we describe a new system (ASPIS) composed by a 4-CCD spectral sensor, a thermal IR camera and a laser altimeter that is mounted on a flexible Sky-Arrow airplane. A test application of the multispectral sensor to estimate durum wheat quality is also presented.
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Indium tin oxide (ITO) biosensors are used to perform simultaneous optical and electrical measurements in order to examine the dynamic cellular attachment, spreading, and proliferation of endothelial cells (ECs) as well as cytotoxic effects when exposed to cytochalasin D. A detailed description of

Indium tin oxide (ITO) biosensors are used to perform simultaneous optical and electrical measurements in order to examine the dynamic cellular attachment, spreading, and proliferation of endothelial cells (ECs) as well as cytotoxic effects when exposed to cytochalasin D. A detailed description of the fabrication of these sensors is provided and their superior optical characteristics are qualitatively shown using four different microscopic images. Differential interference contrast microscopy (DICM) images were acquired simultaneously with micro-impedance measurements as a function of frequency and time. A digital image processing algorithm quantified the cell-covered electrode area as a function of time. In addition, cytotoxicity effects, produced by the toxic agent cytochalasin D, were examined using micro-impedance measurements, confocal microscopy images of stained actin-filaments, and interference reflection contrast microscopy (IRCM) capable of examining the bottom morphology of a cell. The results of this study show (1) the dynamic optical and electrical cellular characteristics using optically thin ITO biosensors; (2) qualitative agreement between cell-covered electrode area and electrical impedance during cellular attachment; (3) in vitro cytotoxicity detection of ECs due to 3 mM cytochalasin D. The present opto-electric biosensor system is unique in that a simultaneous and integrated cellular analysis is possible for a variety of living cells.
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Geographical Information Systems (GIS) have been gaining a growing interest in Turkey. Many local governments and public agencies have been struggling to set up such systems to serve the needs and meet public requirements. Urban life shelters the advertisement reality which is presented

Geographical Information Systems (GIS) have been gaining a growing interest in Turkey. Many local governments and public agencies have been struggling to set up such systems to serve the needs and meet public requirements. Urban life shelters the advertisement reality which is presented at various places, on vehicles, shops etc. in daily life. It can be said that advertisement is a part of daily life in urban area, especially in city centers. In addition, one of the main sources of revenue for municipalities comes from advertising and notices. The advertising sector provides a great level of income today. Therefore advertising is individually very important for local governments and urban management. Although it is valuable for local governments, it is also very important for urban management to place these advertisement signs and billboards in an orderly fashion which is pleasing to the eye. Another point related to this subject is the systematic control mechanism which is necessary for collecting taxes regularly and updating. In this paper, first practical meaning of notice and advertisement subject, problem definition and objectives are described and then legal support and daily practice are revised. Current practice and problems are mentioned. Possibilities of measuring and obtaining necessary information by using digital images and transferring them to spatial databases are studied. By this study, a modern approach was developed for urban management and municipalities by using information technology which is an alternative to current application. Criteria which provide environmental harmony such as urban beauty, colour, compatibility and safety were also evaluated. It was finally concluded that measuring commercial signs and keeping environmental harmony under control for urban beauty can be provided by Digital Photogrammetry (DP) technique and GIS capabilities which were studied with pilot applications in the city center of Ankara.
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Near Infrared Hyperspectral Imaging (NIRHSI) is an emerging technology platform that integrates conventional imaging and spectroscopy to attain both spatial and spectral information from an object. Two important problems in NIRHSI are those of data load and unserviceable pixels in the NIR sensor.

Near Infrared Hyperspectral Imaging (NIRHSI) is an emerging technology platform that integrates conventional imaging and spectroscopy to attain both spatial and spectral information from an object. Two important problems in NIRHSI are those of data load and unserviceable pixels in the NIR sensor. Hyperspectral imaging experiments generate large amounts of data (typically > 50 MB per image), which tend to overwhelm the memory capacity of conventional computer systems. This inhibits the utilisation of NIRHSI for routine online industrial application. In general, approximately 1% of pixels in NIR detectors are unserviceable or ‘dead’, containing no useful information. While this percentage of pixels is insignificant for single wavelength imaging, the problem is amplified in NIRHSI, where > 100 wavelength images are typically acquired. This paper describes an approach for reducing the data load of hyperspectral experiments by using sample-specific vector-to-scalar operators for real time feature extraction and a systematic procedure for compensating for ‘dead’ pixels in the NIR sensor. The feasibility of this approach was tested for prediction of moisture content in carrot tissue.
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This study aims at comparing the capability of different sensors to detect land cover materials within an historical urban center. The main objective is to evaluate the added value of hyperspectral sensors in mapping a complex urban context. In this study we used:

This study aims at comparing the capability of different sensors to detect land cover materials within an historical urban center. The main objective is to evaluate the added value of hyperspectral sensors in mapping a complex urban context. In this study we used: (a) the ALI and Hyperion satellite data, (b) the LANDSAT ETM+ satellite data, (c) MIVIS airborne data and (d) the high spatial resolution IKONOS imagery as reference. The Venice city center shows a complex urban land cover and therefore was chosen for testing the spectral and spatial characteristics of different sensors in mapping the urban tissue. For this purpose, an object-oriented approach and different common classification methods were used. Moreover, spectra of the main anthropogenic surfaces (i.e. roofing and paving materials) were collected during the field campaigns conducted on the study area. They were exploited for applying band-depth and sub-pixel analyses to subsets of Hyperion and MIVIS hyperspectral imagery. The results show that satellite data with a 30m spatial resolution (ALI, LANDSAT ETM+ and HYPERION) are able to identify only the main urban land cover materials.
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The sea surface imprints of Atmospheric Vortex Street (AVS) off Aleutian Volcanic Islands, Alaska were observed in two RADARSAT-1 Synthetic Aperture Radar (SAR) images separated by about 11 hours. In both images, three pairs of distinctive vortices shedding in the lee side of

The sea surface imprints of Atmospheric Vortex Street (AVS) off Aleutian Volcanic Islands, Alaska were observed in two RADARSAT-1 Synthetic Aperture Radar (SAR) images separated by about 11 hours. In both images, three pairs of distinctive vortices shedding in the lee side of two volcanic mountains can be clearly seen. The length and width of the vortex street are about 60-70 km and 20 km, respectively. Although the AVS’s in the two SAR images have similar shapes, the structure of vortices within the AVS is highly asymmetrical. The sea surface wind speed is estimated from the SAR images with wind direction input from Navy NOGAPS model. In this paper we present a complete MM5 model simulation of the observed AVS. The surface wind simulated from the MM5 model is in good agreement with SAR-derived wind. The vortex shedding rate calculated from the model run is about 1 hour and 50 minutes. Other basic characteristics of the AVS including propagation speed of the vortex, Strouhal and Reynolds numbers favorable for AVS generation are also derived. The wind associated with AVS modifies the cloud structure in the marine atmospheric boundary layer. The AVS cloud pattern is also observed on a MODIS visible band image taken between the two RADARSAT SAR images. An ENVISAT advance SAR image taken 4 hours after the second RADARSAT SAR image shows that the AVS has almost vanished.
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A non-invasive glucose measurement system based on the method of metabolic heat conformation (MHC) is presented in this paper. This system consists of three temperature sensors, two humidity sensors, an infrared sensor and an optical measurement device. The glucose level can be deduced

A non-invasive glucose measurement system based on the method of metabolic heat conformation (MHC) is presented in this paper. This system consists of three temperature sensors, two humidity sensors, an infrared sensor and an optical measurement device. The glucose level can be deduced from the quantity of heat dissipation, blood flow rate of local tissue and degree of blood oxygen saturation. The methodology of the data process and the measurement error are also analyzed. The system is applied in a primary clinical test. Compared with the results of a commercial automated chemistry analyzer, the correlation coefficient of the collected data from the system is 0.856. Result shows that the correlation coefficient improves when the factor of heat dissipated by evaporation of the skin is added in. A non-invasive method of measuring the blood flow rate of local tissue by heat transmission between skin and contacted conductor is also introduced. Theoretical derivation and numerical simulation are completed as well. The so-called normalized difference mean (NDM) is chosen to express the quantity of the blood flow rate. The correlation coefficient between the blood flow rates by this method and the results of a Doppler blood flow meter is equal to 0.914.
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Infrared temperature sensors, simple device for temperature measurement, have been modified for the measurement of temperature distribution on the metal surface in a way of nondestructive detection of defects of the object. In this study, the IR sensor system is utilized for the

Infrared temperature sensors, simple device for temperature measurement, have been modified for the measurement of temperature distribution on the metal surface in a way of nondestructive detection of defects of the object. In this study, the IR sensor system is utilized for the defect detection in a cylinder with one point heating, and the performance of the system is examined with an aluminum cylinder having a simulated defect. In addition, a 3-D conduction equation is numerically solved to compare the computed temperature profile with the measured one. The experimental outcome indicates that the defect detection is readily available with the proposed device and the point heating is practical for the applications of the defect detection. It is also found that the measured temperature distribution is comparable to the computed result from the conduction equation.
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This paper presents an experimental Synthetic Aperture Radar (SAR) system that is under development in the Universidad Politécnica de Madrid. The system uses Linear Frequency Modulated Continuous Wave (LFM-CW) radar with a two antenna configuration for transmission and reception. The radar operates in

This paper presents an experimental Synthetic Aperture Radar (SAR) system that is under development in the Universidad Politécnica de Madrid. The system uses Linear Frequency Modulated Continuous Wave (LFM-CW) radar with a two antenna configuration for transmission and reception. The radar operates in the millimeter-wave band with a maximum transmitted bandwidth of 2 GHz. The proposed system is being developed for Unmanned Aerial Vehicle (UAV) operation. Motion errors in UAV operation can be critical. Therefore, this paper proposes a method for focusing SAR images with movement errors larger than the resolution cell. Typically, this problem is solved using two processing steps: first, coarse motion compensation based on the information provided by an Inertial Measuring Unit (IMU); and second, fine motion compensation for the residual errors within the resolution cell based on the received raw data. The proposed technique tries to focus the image without using data of an IMU. The method is based on a combination of the well known Phase Gradient Autofocus (PGA) for SAR imagery and typical algorithms for translational motion compensation on Inverse SAR (ISAR). This paper shows the first real experiments for obtaining high resolution SAR images using a car as a mobile platform for our radar.
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The main objective of this project is to implement the multiple fan beam projection technique using optical fibre sensors with the aim to achieve a high data acquisition rate. Multiple fan beam projection technique here is defined as allowing more than one emitter

The main objective of this project is to implement the multiple fan beam projection technique using optical fibre sensors with the aim to achieve a high data acquisition rate. Multiple fan beam projection technique here is defined as allowing more than one emitter to transmit light at the same time using the switch-mode fan beam method. For the thirty-two pairs of sensors used, the 2-projection technique and 4- projection technique are being investigated. Sixteen sets of projections will complete one frame of light emission for the 2-projection technique while eight sets of projection will complete one frame of light emission for the 4-projection technique. In order to facilitate data acquisition process, PIC microcontroller and the sample and hold circuit are being used. This paper summarizes the hardware configuration and design for this project.
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High range resolution (HRR) profiling using stepped-frequency pulse trains suffers from range shift and the attenuation/dispersion of range profiles while the target of interest is moving. To overcome these two drawbacks, a new algorithm based on the maximum likelihood (ML) estimation is proposed

High range resolution (HRR) profiling using stepped-frequency pulse trains suffers from range shift and the attenuation/dispersion of range profiles while the target of interest is moving. To overcome these two drawbacks, a new algorithm based on the maximum likelihood (ML) estimation is proposed in this paper. Without altering the conventional stepped-frequency waveform, this algorithm can estimate the target velocity and thereby compensate the phase errors caused by the target’s motion. It is shown that the velocity can be accurately estimated and the range profile can be correctly reconstructed.
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In this work, a 2-D subaperture polar format algorithm (PFA) based on steppedchirp signal is proposed. Instead of traditional pulse synthesis preprocessing, the presented method integrates the pulse synthesis process into the range subaperture processing. Meanwhile, due to the multi-resolution property of subaperture

In this work, a 2-D subaperture polar format algorithm (PFA) based on steppedchirp signal is proposed. Instead of traditional pulse synthesis preprocessing, the presented method integrates the pulse synthesis process into the range subaperture processing. Meanwhile, due to the multi-resolution property of subaperture processing, this algorithm is able to compensate the space-variant phase error caused by the radar motion during the period of a pulse cluster. Point target simulation has validated the presented algorithm.
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Soil compaction is an important physical limiting factor for the root growth and plant emergence and is one of the major causes for reduced crop yield worldwide. The objective of this study was to generate 2D/3D soil compaction maps for different depth layers

Soil compaction is an important physical limiting factor for the root growth and plant emergence and is one of the major causes for reduced crop yield worldwide. The objective of this study was to generate 2D/3D soil compaction maps for different depth layers of the soil. To do so, a soil penetrometer was designed, which was mounted on the three-point hitch of an agricultural tractor, consisting of a mechanical system, data acquisition system (DAS), and 2D/3D imaging and analysis software. The system was successfully tested in field conditions, measuring soil penetration resistances as a function of depth from 0 to 40 cm at 1 cm intervals. The software allows user to either tabulate the measured quantities or generate maps as soon as data collection has been terminated. The system may also incorporate GPS data to create geo-referenced soil maps. The software enables the user to graph penetration resistances at a specified coordinate. Alternately, soil compaction maps could be generated using data collected from multiple coordinates. The data could be automatically stratified to determine soil compaction distribution at different layers of 5, 10,.…, 40 cm depths. It was concluded that the system tested in this study could be used to assess the soil compaction at topsoil and the randomly distributed hardpan formations just below the common tillage depths, enabling visualization of spatial variability through the imaging software.
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Water monitoring at the scale of a small agricultural region is a key point to insure a good crop development particularly in South-Eastern France, where extreme climatic conditions result in long dry periods in spring and summer with very sparse precipitation events, corresponding

Water monitoring at the scale of a small agricultural region is a key point to insure a good crop development particularly in South-Eastern France, where extreme climatic conditions result in long dry periods in spring and summer with very sparse precipitation events, corresponding to a crucial period of crop development. Remote sensing with the increasing imagery resolution is a useful tool to provide information on plant water status over various temporal and spatial scales. The current study focussed on assessing the potentialities of FORMOSAT-2 data, characterized by high spatial (8m pixel) and temporal resolutions (1-3 day/time revisit), to improve crop modeling and spatial estimation of the main land properties. Thirty cloud free images were acquired from March to October 2006 over a small region called Crau-Camargue in SE France, while numerous ground measurements were performed simultaneously over various crop types. We have compared two models simulating energy transfers between soil, vegetation and atmosphere: SEBAL and PBLs. Maps of evapotranspiration were analyzed according to the agricultural practices at field scale. These practices were well identified from FORMOSAT-2 images, which provided accurate input surface parameters to the SVAT models.
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It is important to understand reflective properties of snow, for example for remote sensing applications and for modeling of energy balances in snow packs. We present a method with which we can compare reflectance measurements and calculations for the same snow sample structures.

It is important to understand reflective properties of snow, for example for remote sensing applications and for modeling of energy balances in snow packs. We present a method with which we can compare reflectance measurements and calculations for the same snow sample structures. Therefore, we first tomograph snow samples to acquire snow structure images (6 x 2 mm). Second, we calculated the sample reflectance by modeling the radiative transfer, using a beam tracing model. This model calculates the biconical reflectance (BR) derived from an arbitrary number of incident beams. The incident beams represent a diffuse light source. We applied our method to four different snow samples: Fresh snow, metamorphosed snow, depth hoar, and wet snow. The results show that (i) the calculated and measured reflectances agree well and (ii) the model produces different biconical reflectances for different snow types. The ratio of the structure to the wavelength is large. We estimated that the size parameter is larger than 50 in all cases we analyzed. Specific surface area of the snow samples explains most of the difference in radiance, but not the different biconical reflectance distributions. The presented method overcomes the limitations of common radiative transfer models which use idealized grain shapes such as spheres, plates, needles and hexagonal particles. With this method we could improve our understanding for changes in biconical reflectance distribution associated with changes in specific surface area.
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Remote sensing offers a cost efficient means for identifying and monitoring wetlands over a large area and at different moments in time. In this study, we aim at providing ecologically relevant information on characteristics of temporary and permanent isolated open water wetlands, obtained

Remote sensing offers a cost efficient means for identifying and monitoring wetlands over a large area and at different moments in time. In this study, we aim at providing ecologically relevant information on characteristics of temporary and permanent isolated open water wetlands, obtained by standard techniques and relatively cheap imagery. The number, surface area, nearest distance, and dynamics of isolated temporary and permanent wetlands were determined for the Western Cape, South Africa. Open water bodies (wetlands) were mapped from seven Landsat images (acquired during 1987 – 2002) using supervised maximum likelihood classification. The number of wetlands fluctuated over time. Most wetlands were detected in the winter of 2000 and 2002, probably related to road constructions. Imagery acquired in summer contained fewer wetlands than in winter. Most wetlands identified from Landsat images were smaller than one hectare. The average distance to the nearest wetland was larger in summer. In comparison to temporary wetlands, fewer, but larger permanent wetlands were detected. In addition, classification of non-vegetated wetlands on an Envisat ASAR radar image (acquired in June 2005) was evaluated. The number of detected small wetlands was lower for radar imagery than optical imagery (acquired in June 2002), probably because of deterioration of the spatial information content due the extensive pre-processing requirements of the radar image. Both optical and radar classifications allow to assess wetland characteristics that potentially influence plant and animal metacommunity structure. Envisat imagery, however, was less suitable than Landsat imagery for the extraction of detailed ecological information, as only large wetlands can be detected. This study has indicated that ecologically relevant data can be generated for the larger wetlands through relatively cheap imagery and standard techniques, despite the relatively low resolution of Landsat and Envisat imagery. For the characterisation of very small wetlands, high spatial resolution optical or radar images are needed. This study exemplifies the benefits of integrating remote sensing and ecology and hence stimulates interdisciplinary research of isolated wetlands.
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This paper outlines how light Unmanned Aerial Vehicles (UAV) can be used in remote sensing for precision farming. It focuses on the combination of simple digital photographic cameras with spectral filters, designed to provide multispectral images in the visible and near-infrared domains. In

This paper outlines how light Unmanned Aerial Vehicles (UAV) can be used in remote sensing for precision farming. It focuses on the combination of simple digital photographic cameras with spectral filters, designed to provide multispectral images in the visible and near-infrared domains. In 2005, these instruments were fitted to powered glider and parachute, and flown at six dates staggered over the crop season. We monitored ten varieties of wheat, grown in trial micro-plots in the South-West of France. For each date, we acquired multiple views in four spectral bands corresponding to blue, green, red, and near-infrared. We then performed accurate corrections of image vignetting, geometric distortions, and radiometric bidirectional effects. Afterwards, we derived for each experimental micro-plot several vegetation indexes relevant for vegetation analyses. Finally, we sought relationships between these indexes and field-measured biophysical parameters, both generic and date-specific. Therefore, we established a robust and stable generic relationship between, in one hand, leaf area index and NDVI and, in the other hand, nitrogen uptake and GNDVI. Due to a high amount of noise in the data, it was not possible to obtain a more accurate model for each date independently. A validation protocol showed that we could expect a precision level of 15% in the biophysical parameters estimation while using these relationships.
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Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the

Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface–atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF) and Particle filter (PF), for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law) and could be a strong alternative to EnKF which is subject to some limitations including the linear updating rule and assumption of jointly normal distribution of errors in state variables and observation.
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The Indian Ocean tsunami (2004) and Hurricane Katrina (2005) reveal the coming of age of the on-line disaster response community. Due to the integration of key geospatial technologies (remote sensing - RS, geographic information systems - GIS, global positioning systems – GPS) and the Internet, on-line disaster response communities have grown. They include the traditional aspects of disaster preparedness, response, recovery, mitigation, and policy as facilitated by governmental agencies and relief response organizations. However, the contribution from the public via the Internet has changed significantly. The on-line disaster response community includes several key characteristics: the ability to donate money quickly and efficiently due to improved Internet security and reliable donation sites; a computer-savvy segment of the public that creates blogs, uploads pictures, and disseminates information – oftentimes faster than government agencies, and message boards to create interactive information exchange in seeking family members and identifying shelters. A critical and novel occurrence is the development of “people as sensors” - networks of government, NGOs, private companies, and the public - to build rapid response databases of the disaster area for various aspects of disaster relief and response using geospatial technologies. This paper examines these networks, their products, and their future potential.
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Near-infrared fluorescent (NIRF) materials are promising labeling reagents for sensitive determination and imaging of biological targets. In the near-infrared region biological samples have low background fluorescence signals, providing high signal to noise ratio. Meanwhile, near-infrared radiation can penetrate into sample matrices deeply due to low light scattering. Thus, in vivo and in vitro imaging of biological samples can be achieved by employing the NIRF probes. To take full advantage of NIRF materials in the biological and biomedical field, one of the key issues is to develop intense and biocompatible NIRF probes. In this review, a number of NIRF materials are discussed including traditional NIRF dye molecules, newly developed NIRF quantum dots and single-walled carbon nanotubes, as well as rare earth metal compounds. The use of some NIRF materials in various nanostructures is illustrated. The enhancement of NIRF using metal nanostructures is covered as well. The fluorescence mechanism and bioapplications of each type of the NIRF materials are discussed in details.
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Implantable devices such as cardiac pacemakers, drug-delivery systems, and defibrillators have had a tremendous impact on the quality of live for many disabled people. To date, many devices have been developed for implantation into various parts of the human body. In this paper,

Implantable devices such as cardiac pacemakers, drug-delivery systems, and defibrillators have had a tremendous impact on the quality of live for many disabled people. To date, many devices have been developed for implantation into various parts of the human body. In this paper, we focus on devices implanted in the head. In particular, we describe the technologies necessary to create implantable microimagers. Design, fabrication, and implementation issues are discussed vis-à-vis two examples of implantable microimagers; the retinal prosthesis and in vivo neuro-microimager. Testing of these devices in animals verify the use of the microimagers in the implanted state. We believe that further advancement of these devices will lead to the development of a new method for medical and scientific applications.
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Optical technologies can be developed as practical tools for monitoring plant health by providing unique spectral signatures that can be related to specific plant stresses. Signatures from thermal and fluorescence imaging have been used successfully to track pathogen invasion before visual symptoms are

Optical technologies can be developed as practical tools for monitoring plant health by providing unique spectral signatures that can be related to specific plant stresses. Signatures from thermal and fluorescence imaging have been used successfully to track pathogen invasion before visual symptoms are observed. Another approach for noninvasive plant health monitoring involves elucidating the manner with which light interacts with the plant leaf and being able to identify changes in spectral characteristics in response to specific stresses. To achieve this, an important step is to understand the biochemical and anatomical features governing leaf reflectance, transmission and absorption. Many studies have opened up possibilities that subtle changes in leaf reflectance spectra can be analyzed in a plethora of ways for discriminating nutrient and water stress, but with limited success. There has also been interest in developing transgenic phytosensors to elucidate plant status in relation to environmental conditions. This approach involves unambiguous signal creation whereby genetic modification to generate reporter plants has resulted in distinct optical signals emitted in response to specific stressors. Most of these studies are limited to laboratory or controlled greenhouse environments at leaf level. The practical translation of spectral cues for application under field conditions at canopy and regional levels by remote aerial sensing remains a challenge. The movement towards technology development is well exemplified by the Controlled Ecological Life Support System under development by NASA which brings together technologies for monitoring plant status concomitantly with instrumentation for environmental monitoring and feedback control.
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The increased availability of remote sensing platforms with appropriate spatial and temporal resolution, global coverage and low financial costs allows for fast, semi-automated, and cost-effective estimates of changes in glacier parameters over large areas. Remote sensing approaches allow for regular monitoring of the

The increased availability of remote sensing platforms with appropriate spatial and temporal resolution, global coverage and low financial costs allows for fast, semi-automated, and cost-effective estimates of changes in glacier parameters over large areas. Remote sensing approaches allow for regular monitoring of the properties of alpine glaciers such as ice extent, terminus position, volume and surface elevation, from which glacier mass balance can be inferred. Such methods are particularly useful in remote areas with limited field-based glaciological measurements. This paper reviews advances in the use of visible and infrared remote sensing combined with field methods for estimating glacier parameters, with emphasis on volume/area changes and glacier mass balance. The focus is on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensor and its applicability for monitoring Himalayan glaciers. The methods reviewed are: volumetric changes inferred from digital elevation models (DEMs), glacier delineation algorithms from multi-spectral analysis, changes in glacier area at decadal time scales, and AAR/ELA methods used to calculate yearly mass balances. The current limitations and on-going challenges in using remote sensing for mapping characteristics of mountain glaciers also discussed, specifically in the context of the Himalaya.
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Microcantilevers were first introduced as imaging probes in Atomic Force Microscopy (AFM) due to their extremely high sensitivity in measuring surface forces. The versatility of these probes, however, allows the sensing and measurement of a host of mechanical properties of various materials. Sensor

Microcantilevers were first introduced as imaging probes in Atomic Force Microscopy (AFM) due to their extremely high sensitivity in measuring surface forces. The versatility of these probes, however, allows the sensing and measurement of a host of mechanical properties of various materials. Sensor parameters such as resonance frequency, quality factor, amplitude of vibration and bending due to a differential stress can all be simultaneously determined for a cantilever. When measuring the mechanical properties of materials, identifying and discerning the most influential parameters responsible for the observed changes in the cantilever response are important. We will, therefore, discuss the effects of various force fields such as those induced by mass loading, residual stress, internal friction of the material, and other changes in the mechanical properties of the microcantilevers. Methods to measure variations in temperature, pressure, or molecular adsorption of water molecules are also discussed. Often these effects occur simultaneously, increasing the number of parameters that need to be concurrently measured to ensure the reliability of the sensors. We therefore systematically investigate the geometric and environmental effects on cantilever measurements including the chemical nature of the underlying interactions. To address the geometric effects we have considered cantilevers with a rectangular or circular cross section. The chemical nature is addressed by using cantilevers fabricated with metals and/or dielectrics. Selective chemical etching, swelling or changes in Young’s modulus of the surface were investigated by means of polymeric and inorganic coatings. Finally to address the effect of the environment in which the cantilever operates, the Knudsen number was determined to characterize the molecule-cantilever collisions. Also bimaterial cantilevers with high thermal sensitivity were used to discern the effect of temperature variations. When appropriate, we use continuum mechanics, which is justified according to the ratio between the cantilever thickness and the grain size of the materials. We will also address other potential applications such as the ageing process of nuclear materials, building materials, and optical fibers, which can be investigated by monitoring their mechanical changes with time. In summary, by virtue of the dynamic response of a miniaturized cantilever shaped material, we present useful measurements of the associated elastic properties.
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